AI Infrastructure Field Solutions Architect – Cloud

Google LLC; Kirkland (WA); On-site; USD 233,000 - 324,000; Full time

Benefits offered by this job

Health, dental, vision, life, and DIS/

401(k) with company match

Paid Time Off: 20 days/year

Sick Time: 40 hours/year

Maternity Leave: 28-30 weeks

Baby Bonding Leave: 18 weeks

Holidays: 13 paid days

Job summary

Google LLC is seeking an AI Infrastructure Field Solution Architect to accelerate TPU/GPU deployments for enterprise customers. You will guide technical discussions on network topology, fabric architecture, and compute/storage integration while supporting server provisioning.

On-site work is required with potential travel for client facilities; you will partner with internal teams to remove roadblocks and shape platform roadmaps, helping customers adopt AI accelerators at scale.

Qualifications

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• 10 years of experience with data center technologies, solutions and their deployment.
• Experience with data center networking, such as routing, switching, DNS, and IP addressing; compute and storage concepts; and operations including power, cooling, and procedures.
• Experience with AI model training and inference, deploying OSS frameworks such as PyTorch, Jax, etc., and optimizing performance versus costs.
• Experience with scripting and coding in Python, YAML, and Kubernetes.

Responsibilities

• Learn more about benefits at Google .
• Act as a trusted advisor to customers, helping them understand and incorporate AI accelerators into their overall business strategy by designing training and inferencing platforms, and incorporating customers' existing data center technologies.
• Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on Proofs of Concept, demonstrating features, optimizing model performance, profiling, and benchmarking.
• Assist in production deployment of Google Cloud accelerators, troubleshoot integration issues with existing compute, networking, and storage solutions, and enable customers to operate their training and inferencing clusters successfully.
• Build repeatable assets to enable other customers and internal teams.
• Collaborate with the AI Infrastructure Dedicated Engineering Team in Google Compute Engine, and scale ML techniques and solutions broadly. Influence Google Cloud strategy at the intersection of infrastructure and AI by advocating for enterprise customer requirements.

Skills

Data center technologies

Data center networking

AI model training & inference

Python scripting

YAML

Kubernetes

Education

Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience

Tools

PyTorch

JAX

Kubernetes

Job description

Google LLC is seeking an AI Infrastructure Field Solution Architect to accelerate TPU/GPU deployments for enterprise customers. You will guide technical discussions on network topology, fabric architecture, and compute/storage integration while supporting server provisioning.

On-site work is required with potential travel for client facilities; you will partner with internal teams to remove roadblocks and shape platform roadmaps, helping customers adopt AI accelerators at scale.